Method, apparatus and computer program product for differential policy enforcement for roadways

ABSTRACT

A method, apparatus and computer program product are provided for enforcing a differential policy for autonomous vehicles along a road. In the context of a method, the may include: determining location information of a vehicle including a road segment and a direction of travel; identifying capabilities of sensors of the vehicle; determining an autonomous or semi-autonomous policy for the road segment specific to the vehicle in response to identifying the capabilities of the sensors of the vehicle; providing a first set of instructions for autonomous control in response to the capabilities of the sensors of the vehicle satisfying a first level of capability; and providing a second set of instructions for autonomous control in response to the capabilities of the sensors of the vehicle satisfying a second level of capability.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 16/059,350, filed on Aug. 9, 2018, the contents ofwhich are hereby incorporated by reference in their entirety.

TECHNOLOGICAL FIELD

An example embodiment of the present invention relates generally toenforcing policies on roadways relating to vehicle control along theroadways, and more particularly, to a method of differential policyenforcement for vehicle control along roadways between manually drivenvehicles and autonomous or semi-autonomously controlled vehicles.

BACKGROUND

Maps have been used for centuries for providing route geometry andgeographical information, while routes have been driven by peoplereferencing the maps primarily for direction and orientation.Conventional paper maps including static images of roadways andgeographic features from a snapshot in history have given way to digitalmaps presented on computers and mobile devices, and navigation has beenenhanced through the use of graphical user interfaces.

Digital maps and navigation can provide dynamic route guidance to usersas they travel along a route, or general assistance to a user when nospecific destination has been selected. Further, dynamic map attributessuch as route traffic, route conditions, and other dynamic map-relatedinformation may be provided to enhance the digital maps and facilitatenavigation and driver assistance through situational awareness. Typicaldigital maps and navigation systems may have copious amounts ofinformation available, from various road network awareness to accident,construction, and other traffic-related dynamically updated data.Further, the ubiquity of available data results in a copious amount ofdata and information pertaining to road segments and objects that may befound within an area represented by a map. The volume of associated datamay be overwhelming for mapping software or navigation systems, but maybe used in ways that facilitate autonomous and semi-autonomous vehiclecontrol.

BRIEF SUMMARY

A method, apparatus, and computer program product are therefore providedfor implementing differential policies for road segments relating tovehicles traveling along the road segments. Embodiments described hereinmay provide an apparatus to facilitate autonomous or semi-autonomouscontrol of a vehicle including at least one processor and at least onenon-transitory memory including computer program code instructions. Thecomputer program code instructions may be configured to, when executed,cause the apparatus to: determine location information of a vehicleincluding a road segment and a direction of travel; identifycapabilities of sensors of the vehicle; determine an autonomous orsemi-autonomous policy for the road segment specific to the vehicle inresponse to identifying the capabilities of the sensors of the vehicle;provide a first set of instructions for autonomous vehicle control inresponse to the capabilities of the sensors of the vehicle satisfying afirst level of capability; and provide a second set of instructions forautonomous vehicle control in response to the capabilities of thesensors of the vehicle satisfying a second level of capability.

According to some embodiments, the first level of capability of sensorsof a vehicle may be associated with a first sensor package, where thesecond level of capability of sensors of a vehicle may be associatedwith a second sensor packate. Causing the apparatus to identifycapabilities of sensors of a vehicle may include causing the apparatusto identify a sensor package of the vehicle. Causing the apparatus toprovide a first set of autonomous instructions may include instructionsfor traveling at a first speed along the road segment and causing theapparatus to provide a second set of autonomous instructions may includeinstructions for traveling at a second speed along the road segment,different from the first speed. The first road segment may include afirst speed limit for vehicles equipped with the first sensor package,and a second speed limit different from the first speed limit forvehicles equipped with the second sensor package.

The apparatus of some embodiments may be caused to: determine at leastone of a time of day or a weather condition, where causing the apparatusto determine an autonomous or semi-autonomous policy for the roadsegment may include causing the apparatus to determine an autonomous orsemi-autonomous policy for the road segment based, at least in part, onthe determined time of day or weather condition. The apparatus may becaused to determine a traffic level along the road segment in thedirection of travel of the vehicle, where causing the apparatus todetermine an autonomous or semi-autonomous policy for the road segmentmay include causing the apparatus to determine an autonomous orsemi-autonomous policy for the road segment based, at least in part, onthe determined traffic level along the road segment. Causing theapparatus to determine an autonomous or semi-autonomous policy for theroad segment specific to the vehicle in response to identifying thecapabilities of the sensors of the vehicle may include causing theapparatus to: access map data including road segment policy information;and retrieve road segment policy information associated with the roadsegment and the direction of travel.

Embodiments described herein may provide a computer program productincluding at least one non-transitory computer-readable storage mediumhaving computer-executable program code instructions stored therein. Thecomputer-executable program code instructions include program codeinstructions to: determine location information of a vehicle including aroad segment and a direction of travel; identify capabilities of sensorsof the vehicle; determine an autonomous or semi-autonomous policy forthe road segment specific to the vehicle in response to identifying thecapabilities of the sensors of the vehicle; provide a first set ofinstructions for autonomous control in response to the capabilities ofthe sensors of the vehicle satisfying a first level of capability; andprovide a second set of instructions for autonomous control in responseto the capabilities of the sensors of the vehicle satisfying a secondlevel of capability.

According to some embodiments, the first level of capability of thesensors of a vehicle is associated with a first sensor package, wherethe second level of capability of sensors of a vehicle is associatedwith a second sensor package. Identifying capabilities of sensors of avehicle may include identifying a sensor package of the vehicle. Theprogram code instructions to provide a first set of autonomousinstructions may include instructions for traveling at a first speedalong the road segment and the program code instructions to provide asecond set of autonomous instructions may include instructions fortraveling at a second speed along the road segment, different from thefirst speed. The first road segment may include a first speed limit forvehicles equipped with the first sensor package and a second speedlimit, different from the first speed limit, for vehicles equipped withthe second sensor package.

The computer program product of some embodiments may include programcode instructions to: determine at least one of a time of day or aweather condition, where the program code instructions to determine anautonomous or semi-autonomous policy for the road segment may includeprogram code instructions to determine an autonomous or semi-autonomouspolicy for the road segment based, at least in part, on the determinedtime of day or the weather condition. Embodiments may include programcode instructions to: determine a traffic level along the road segmentin the direction of travel of the vehicle, where the program codeinstructions to determine an autonomous or semi-autonomous policy forthe road segment may include program code instructions to determine anautonomous or semi-autonomous policy for the road segment based, atleast in part, on the determined traffic level along the road segment.The program code instructions to determine an autonomous orsemi-autonomous policy for the road segment specific to the vehicle inresponse to identifying the capabilities of the sensors of the vehiclemay include program code instructions to: access map data including roadsegment policy information; and retrieve road segment policy informationassociated with the road segment and the direction of travel.

Embodiments described herein may provide a method including: determininglocation information of a vehicle including a road segment and adirection of travel; identifying capabilities of sensors of the vehicle;determining an autonomous or semi-autonomous policy for the road segmentspecific to the vehicle in response to identifying the capabilities ofthe sensors of the vehicle; providing a first set of instructions forautonomous control in response to the capabilities of the sensors of thevehicle satisfying a first level of capability; and providing a secondset of instructions for autonomous control in response to thecapabilities of the sensors of the vehicle satisfying a second level ofcapability.

According to some embodiments, the first level of capability of sensorsof a vehicle is associated with a first sensor package, and the secondlevel of capability of sensors of a vehicle is associated with a secondsensor package, where identifying capabilities of the sensors of avehicle may include identifying a sensor package of the vehicle.Providing a first set of autonomous instructions may includeinstructions for traveling at a first speed along the road segment andproviding a second set of autonomous instructions may includeinstructions for traveling at a second speed along the road segment,different from the first speed. The first road segment may include afirst speed limit for vehicles equipped with the first sensor package,and a second speed limit different from the first speed limit forvehicles equipped with the second sensor package.

Methods may include: determining at least one of a time of day or aweather condition, where determining an autonomous or semi-autonomouspolicy for the road segment may include determining an autonomous orsemi-autonomous policy for the road segment based, at least in part, onthe determined time of day or the weather condition. Methods mayoptionally include determining a traffic level along the road segment inthe direction of travel of the vehicle. Determining an autonomous orsemi-autonomous policy for the road segment may include determining anautonomous or semi-autonomous policy for the road segment based, atleast in part, on the determined level of traffic of the road segment.

Embodiments described herein may provide an apparatus including: meansfor determining location information of a vehicle including a roadsegment and a direction of travel; means for identifying capabilities ofsensors of the vehicle; means for determining an autonomous orsemi-autonomous policy for the road segment specific to the vehicle inresponse to identifying the capabilities of the sensors of the vehicle;means for providing a first set of instructions for autonomous controlin response to the capabilities of the sensors of the vehicle satisfyinga first level of capability; and means for providing a second set ofinstructions for autonomous control in response to the capabilities ofthe sensors of the vehicle satisfying a second level of capability.

According to some embodiments, the first level of capability of sensorsof a vehicle is associated with a first sensor package, and the secondlevel of capability of sensors of a vehicle js associated with a secondsensor package, where the means for identifying capabilities of thesensors of a vehicle may include means for identifying a sensor packageof the vehicle. The means for providing a first set of autonomousinstructions may include means for causing travel at a first speed alongthe road segment and the means for providing a second set of autonomousinstructions may include means for causing travel at a second speedalong the road segment, different from the first speed. The first roadsegment may include a first speed limit for vehicles equipped with thefirst sensor package, and a second speed limit different from the firstspeed limit for vehicles equipped with the second sensor package.

An example apparatus may include: means for determining at least one ofa time of day or a weather condition, where the means for determining anautonomous or semi-autonomous policy for the road segment may includemeans for determining an autonomous or semi-autonomous policy for theroad segment based, at least in part, on the determined time of day orthe weather condition. An apparatus may optionally include means fordetermining a traffic level along the road segment in the direction oftravel of the vehicle. The means for determining an autonomous orsemi-autonomous policy for the road segment may include means fordetermining an autonomous or semi-autonomous policy for the road segmentbased, at least in part, on the determined level of traffic of the roadsegment.

BRIEF DESCRIPTION OF THE DRAWINGS

Having thus described certain example embodiments of the presentinvention in general terms, reference will hereinafter be made to theaccompanying drawings which are not necessarily drawn to scale, andwherein:

FIG. 1 is a block diagram of an apparatus according to an exampleembodiment of the present disclosure;

FIG. 2 is a block diagram of a system for enforcing differential policesalong road segments according to an example embodiment of the presentdisclosure;

FIG. 3 is another block diagram of a system for enforcing differentialpolices along road segments and implementing them in a vehicle accordingto an example embodiment of the present disclosure; and

FIG. 4 is a flowchart of operations for enforcing differential policiesalong road segments according to an example embodiment of the presentdisclosure.

DETAILED DESCRIPTION

Some embodiments of the present invention will now be described morefully hereinafter with reference to the accompanying drawings, in whichsome, but not all, embodiments of the invention are shown. Indeed,various embodiments of the invention may be embodied in many differentforms and should not be construed as limited to the embodiments setforth herein; rather, these embodiments are provided so that thisdisclosure will satisfy applicable legal requirements. Like referencenumerals refer to like elements throughout. As used herein, the terms“data,” “content,” “information,” and similar terms may be usedinterchangeably to refer to data capable of being transmitted, receivedand/or stored in accordance with embodiments of the present invention.Thus, use of any such terms should not be taken to limit the spirit andscope of embodiments of the present invention.

A method, apparatus and computer program product are provided inaccordance with an example embodiment of the present invention forfacilitating autonomous and semi-autonomous driving in an environmentthat shares road segments of a road network with conventional, manuallydriven vehicles. Autonomous vehicles leverage sensor informationrelating to roads to determine safe regions of a road to drive and toevaluate their surroundings as they traverse a road segment. Further,autonomous and semi-autonomous vehicles use high-definition mapinformation to facilitate autonomous driving and to plan autonomousdriving routes. These high-definition maps or HD maps are specificallydesigned and configured to facilitate autonomous and semi-autonomousvehicle control.

HD maps have a high precision at resolutions that may be down to severalcentimeters so as to identify objects proximate a road segment, featuresof a road segment including lane widths, lane markings, trafficdirection, speed limits, lane restrictions, etc. Autonomous andsemi-autonomous vehicles use these HD maps to facilitate the autonomouscontrol features, such as traveling within a lane of a road segment at aprescribed speed limit. Autonomous vehicles may also be equipped with aplurality of sensors to facilitate autonomous vehicle control. Sensorsmay include image sensors/cameras, Light Distancing and Ranging (LiDAR),Global Positioning Systems (GPS), Inertial Measurement Units (IMUs), orthe like which may measure the surroundings of a vehicle and communicateinformation regarding the surroundings to a vehicle control module toprocess and adapt vehicle control accordingly.

FIG. 1 is a schematic diagram of an example apparatus configured forperforming any of the operations described herein. Apparatus 20 is anexample embodiment that may be embodied by or associated with any of avariety of computing devices that include or are otherwise associatedwith a device configured for providing a advanced driver assistancefeatures which may include a navigation system user interface. Forexample, the computing device may be an Advanced Driver AssistanceSystem module (ADAS) which may at least partially control autonomous orsemi-autonomous features of a vehicle; however embodiments of theapparatus may be embodied or partially embodied as a mobile terminal,such as a personal digital assistant (PDA), mobile telephone, smartphone, personal navigation device, smart watch, tablet computer, cameraor any combination of the aforementioned and other types of voice andtext communications systems. In a preferred embodiment the apparatus 20is embodied or partially embodied by an electronic control unit of avehicle that supports safety-critical systems such as the powertrain(engine, transmission, electric drive motors, etc.), steering (e.g.,steering assist or steer-by-wire), and braking (e.g., brake assist orbrake-by-wire). Optionally, the computing device may be a fixedcomputing device, such as a built-in vehicular navigation device,assisted driving device, or the like.

Optionally, the apparatus may be embodied by or associated with aplurality of computing devices that are in communication with orotherwise networked with one another such that the various functionsperformed by the apparatus may be divided between the plurality ofcomputing devices that operate in collaboration with one another.

The apparatus 20 may be equipped with any number of sensors 21, such asa global positioning system (GPS), accelerometer, LiDAR, radar, and/orgyroscope. Any of the sensors may be used to sense information regardingthe movement, positioning, or orientation of the device for use innavigation assistance, as described herein according to exampleembodiments. In some example embodiments, such sensors may beimplemented in a vehicle or other remote apparatus, and the informationdetected may be transmitted to the apparatus 20, such as by near fieldcommunication (NFC) including, but not limited to, Bluetooth™communication, or the like.

The apparatus 20 may include, be associated with, or may otherwise be incommunication with a communication interface 22, processor 24, a memorydevice 26 and a user interface 28. In some embodiments, the processor(and/or co-processors or any other processing circuitry assisting orotherwise associated with the processor) may be in communication withthe memory device via a bus for passing information among components ofthe apparatus. The memory device may be non-transitory and may include,for example, one or more volatile and/or non-volatile memories. In otherwords, for example, the memory device may be an electronic storagedevice (for example, a computer readable storage medium) comprisinggates configured to store data (for example, bits) that may beretrievable by a machine (for example, a computing device like theprocessor). The memory device may be configured to store information,data, content, applications, instructions, or the like for enabling theapparatus to carry out various functions in accordance with an exampleembodiment of the present invention. For example, the memory devicecould be configured to buffer input data for processing by theprocessor. Additionally or alternatively, the memory device could beconfigured to store instructions for execution by the processor.

The processor 24 may be embodied in a number of different ways. Forexample, the processor may be embodied as one or more of varioushardware processing means such as a coprocessor, a microprocessor, acontroller, a digital signal processor (DSP), a processing element withor without an accompanying DSP, or various other processing circuitryincluding integrated circuits such as, for example, an ASIC (applicationspecific integrated circuit), an FPGA (field programmable gate array), amicrocontroller unit (MCU), a hardware accelerator, a special-purposecomputer chip, or the like. As such, in some embodiments, the processormay include one or more processing cores configured to performindependently. A multi-core processor may enable multiprocessing withina single physical package. Additionally or alternatively, the processormay include one or more processors configured in tandem via the bus toenable independent execution of instructions, pipelining and/ormultithreading.

In an example embodiment, the processor 24 may be configured to executeinstructions stored in the memory device 26 or otherwise accessible tothe processor. Alternatively or additionally, the processor may beconfigured to execute hard coded functionality. As such, whetherconfigured by hardware or software methods, or by a combination thereof,the processor may represent an entity (for example, physically embodiedin circuitry) capable of performing operations according to anembodiment of the present invention while configured accordingly. Thus,for example, when the processor is embodied as an ASIC, FPGA or thelike, the processor may be specifically configured hardware forconducting the operations described herein. Alternatively, as anotherexample, when the processor is embodied as an executor of softwareinstructions, the instructions may specifically configure the processorto perform the algorithms and/or operations described herein when theinstructions are executed. However, in some cases, the processor may bea processor of a specific device (for example, the computing device)configured to employ an embodiment of the present invention by furtherconfiguration of the processor by instructions for performing thealgorithms and/or operations described herein. The processor mayinclude, among other things, a clock, an arithmetic logic unit (ALU) andlogic gates configured to support operation of the processor.

The apparatus 20 of an example embodiment may also include or otherwisebe in communication with a user interface 28. The user interface mayinclude a touch screen display, a speaker, physical buttons, and/orother input/output mechanisms. In an example embodiment, the processor24 may comprise user interface circuitry configured to control at leastsome functions of one or more input/output mechanisms. The processorand/or user interface circuitry comprising the processor may beconfigured to control one or more functions of one or more input/outputmechanisms through computer program instructions (for example, softwareand/or firmware) stored on a memory accessible to the processor (forexample, memory device 24, and/or the like). In this regard, theapparatus 20 may interpret positioning data collected by its sensors andprovide a destination preview including visual and audio feedback, to auser, for example.

The apparatus 20 of an example embodiment may also optionally include acommunication interface 22 that may be any means such as a device orcircuitry embodied in either hardware or a combination of hardware andsoftware that is configured to receive and/or transmit data from/toother electronic devices in communication with the apparatus, such as byNFC, described above. Additionally or alternatively, the communicationinterface 22 may be configured to communicate over Global System forMobile Communications (GSM), such as but not limited to Long TermEvolution (LTE). In this regard, the communication interface 22 mayinclude, for example, an antenna (or multiple antennas) and supportinghardware and/or software for enabling communications with a wirelesscommunication network. Additionally or alternatively, the communicationinterface 22 may include the circuitry for interacting with theantenna(s) to cause transmission of signals via the antenna(s) or tohandle receipt of signals received via the antenna(s). In someenvironments, the communication interface 22 may alternatively or alsosupport wired communication or may alternatively support vehicle tovehicle or vehicle to infrastructure wireless links.

The apparatus 20 may support a mapping or navigation application so asto present maps or otherwise provide navigation or driver assistance. Inorder to support a mapping application, the computing device may includeor otherwise be in communication with a geographic database, such as maybe stored in memory 26. For example, the geographic database includesnode data records, road segment or link data records, point of interest(POI) data records, and other data records. More, fewer or differentdata records can be provided. In one embodiment, the other data recordsinclude cartographic data records, routing data, and maneuver data. Oneor more portions, components, areas, layers, features, text, and/orsymbols of the POI or event data can be stored in, linked to, and/orassociated with one or more of these data records. For example, one ormore portions of the POI, event data, or recorded route information canbe matched with respective map or geographic records via position or GPSdata associations (such as using known or future map matching orgeo-coding techniques), for example. Furthermore, other positioningtechnology may be used, such as electronic horizon sensors, radar,LiDAR, ultrasonic and/or infrared sensors.

In example embodiments, a navigation system user interface may beprovided to provide driver assistance to a user traveling along anetwork of roadways. Optionally, embodiments described herein mayprovide assistance for autonomous or semi-autonomous vehicle control.Autonomous vehicle control may include driverless vehicle capabilitywhere all vehicle functions are provided by software and hardware tosafely drive the vehicle along a path identified by the vehicle.Semi-autonomous vehicle control may be any level of driver assistancefrom adaptive cruise control, to lane-keep assist, or the like.Identifying objects along road segments or road links that a vehicle maytraverse may provide information useful to navigation and autonomous orsemi-autonomous vehicle control by establishing barriers definingroadway width, identifying roadway curvature, or any boundary relateddetails of the road links that may be traversed by the vehicle.

A map service provider database may be used to provide driver assistancevia a navigation system and/or through an ADAS having autonomous orsemi-autonomous vehicle control features. FIG. 2 illustrates acommunication diagram of an example embodiment of a system forimplementing example embodiments described herein. The illustratedembodiment of FIG. 2 includes a mobile device 104, which may be, forexample, the apparatus 20 of FIG. 2, such as a mobile phone, anin-vehicle navigation system, an ADAS, or the like, and a map dataservice provider or cloud service 108. Each of the mobile device 104 andmap data service provider 108 may be in communication with at least oneof the other elements illustrated in FIG. 2 via a network 112, which maybe any form of wireless or partially wireless network as will bedescribed further below. Additional, different, or fewer components maybe provided. For example, many mobile devices 104 may connect with thenetwork 112. The map data service provider 108 may be cloud-basedservices and/or may operate via a hosting server that receives,processes, and provides data to other elements of the system.

The map data service provider may include a map database 110 that mayinclude node data, road segment data or link data, point of interest(POI) data, traffic data or the like. The map database 110 may alsoinclude cartographic data, routing data, and/or maneuvering data.According to some example embodiments, the road segment data records maybe links or segments representing roads, streets, or paths, as may beused in calculating a route or recorded route information fordetermination of one or more personalized routes. The node data may beend points corresponding to the respective links or segments of roadsegment data. The road link data and the node data may represent a roadnetwork, such as used by vehicles, cars, trucks, buses, motorcycles,and/or other entities. Optionally, the map database 110 may contain pathsegment and node data records or other data that may representpedestrian paths or areas in addition to or instead of the vehicle roadrecord data, for example. The road/link segments and nodes can beassociated with attributes, such as geographic coordinates, streetnames, address ranges, speed limits, turn restrictions at intersections,and other navigation related attributes, as well as POIs, such asfueling stations, hotels, restaurants, museums, stadiums, offices, autorepair shops, buildings, stores, parks, etc. The map database 110 caninclude data about the POIs and their respective locations in the POIrecords. The map database 110 may include data about places, such ascities, towns, or other communities, and other geographic features suchas bodies of water, mountain ranges, etc. Such place or feature data canbe part of the POI data or can be associated with POIs or POI datarecords (such as a data point used for displaying or representing aposition of a city). In addition, the map database 110 can include eventdata (e.g., traffic incidents, construction activities, scheduledevents, unscheduled events, etc.) associated with the POI data recordsor other records of the map database 110.

The map database 110 may be maintained by a content provider e.g., themap data service provider and may be accessed, for example, by thecontent or service provider processing server 102. By way of example,the map data service provider can collect geographic data and dynamicdata to generate and enhance the map database 110 and dynamic data suchas traffic-related data contained therein. There can be different waysused by the map developer to collect data. These ways can includeobtaining data from other sources, such as municipalities or respectivegeographic authorities, such as via global information system databases.In addition, the map developer can employ field personnel to travel byvehicle along roads throughout the geographic region to observe featuresand/or record information about them, for example. Also, remote sensing,such as aerial or satellite photography and/or LiDAR, can be used togenerate map geometries directly or through machine learning asdescribed herein. However, the most ubiquitous form of data that may beavailable is vehicle data provided by vehicles, such as mobile device104, as they travel the roads throughout a region.

The map database 110 may be a master map database, such as an HD mapdatabase, stored in a format that facilitates updates, maintenance, anddevelopment. For example, the master map database or data in the mastermap database can be in an Oracle spatial format or other spatial format,such as for development or production purposes. The Oracle spatialformat or development/production database can be compiled into adelivery format, such as a geographic data files (GDF) format. The datain the production and/or delivery formats can be compiled or furthercompiled to form geographic database products or databases, which can beused in end user navigation devices or systems.

For example, geographic data may be compiled (such as into a platformspecification format (PSF) format) to organize and/or configure the datafor performing navigation-related functions and/or services, such asroute calculation, route guidance, map display, speed calculation,distance and travel time functions, and other functions, by a navigationdevice, such as by a vehicle represented by mobile device 104, forexample. The navigation-related functions can correspond to vehiclenavigation, pedestrian navigation, or other types of navigation. Thecompilation to produce the end user databases can be performed by aparty or entity separate from the map developer. For example, a customerof the map developer, such as a navigation device developer or other enduser device developer, can perform compilation on a received mapdatabase in a delivery format to produce one or more compiled navigationdatabases.

As mentioned above, the map data service provider 108 map database 110may be a master geographic database, but in alternate embodiments, aclient side map database may represent a compiled navigation databasethat may be used in or with end user devices (e.g., mobile device 104)to provide navigation and/or map-related functions. For example, the mapdatabase 110 may be used with the mobile device 104 to provide an enduser with navigation features. In such a case, the map database 110 canbe downloaded or stored on the end user device which can access the mapdatabase 110 through a wireless or wired connection, such as via aprocessing server 102 and/or the network 112, for example.

In one embodiment, as noted above, the end user device or mobile device104 can be embodied by the apparatus 20 of FIG. 1 and can include anAdvanced Driver Assistance System (ADAS) which may include aninfotainment in-vehicle system or an in-vehicle navigation system,and/or devices such as a personal navigation device (PND), a portablenavigation device, a cellular telephone, a smart phone, a personaldigital assistant (PDA), a watch, a camera, a computer, and/or otherdevice that can perform navigation-related functions, such as digitalrouting and map display. An end user can use the mobile device 104 fornavigation and map functions such as guidance and map display, forexample, and for determination of useful driver assistance information,according to some example embodiments.

Autonomous vehicles or vehicles with some level of autonomous controlsprovide some degree of vehicle control that was previously performed bya person driving a vehicle. Removing some or all of the responsibilitiesof driving from a person and automating those responsibilities require ahigh degree of confidence in performing those responsibilities in amanner at least as good as a human driver. For example, maintaining avehicle's position within a lane by a human involves steering thevehicle between observed lane markings and determining a lane when lanemarkings are faint, absent, or not visible due to weather (e.g., heavyrain, snow, bright sunlight, etc.). A vehicle with autonomous capabilityto keep the vehicle within a lane as it travels along a road segmentmust also be able to identify the lane based on the lane markings orother features that are observable. As such, the autonomous vehicle mustbe equipped with sensors sufficient to observe road features, and acontroller that is capable of processing the signals from the sensorsobserving the road features, interpret those signals, and providevehicle control to maintain the lane position of the vehicle based onthe sensor data. Maintaining lane position is merely one illustrativeexample of a function of autonomous or semi-autonomous vehicles thatdemonstrates the sensor level and complexity of autonomous driving.However, autonomous vehicle capabilities, particularly in fullyautonomous vehicles, must be capable of performing all drivingfunctions. As such, the vehicles must be equipped with sensor packagesthat enable the functionality in a safe manner.

Autonomous and semi-autonomous vehicles may use a variety of sensors tofacilitate various autonomous functions. For example, adaptive cruisecontrol functionality that maintains a following distance from a leadvehicle, and maintains a near-constant speed when not following anothervehicle, requires at least sensors that can detect a vehicle in front ofthe autonomous or semi-autonomous vehicle. Such a sensor may be adistance sensor such as LiDAR or other sensor having similarcapabilities. Further, the autonomous or semi-autonomous vehicle must beequipped with control capabilities to facilitate braking of the vehicleand accelerating the vehicle. This sensor and control system may be a“sensor package” or level of sensor capabilities. Adaptive cruisecontrol has become relatively common, such that a sensor package capableof adaptive cruise control may be a relatively rudimentary level ofsensor capabilities relative to a vehicle that has full autonomouscontrol.

Beyond adaptive cruise control, vehicles with more autonomy may be ableto navigate roadways through lane changes, turns, stopping, starting,and generally performing all features of conventional driving thathistorically have been performed manually by a driver. In order tofacilitate full autonomy, vehicles require a level of sensorcapabilities that can identify road geometry, lane lines, othervehicles, pedestrians, objects in or proximate the roadway, signs, roadanomalies (e.g., temporary construction barricades), etc. Such anadvanced sensor package having a high level of sensor capabilities maybe capable of full autonomous control of a vehicle in a manner thatsubstantially replaces the driver. It is also appreciated that anydegree of autonomy between no autonomy and full autonomy is alsopossible based on a sensor package installed in a vehicle or carriedwith a vehicle and a level of sensor capabilities of the sensor package.

Beyond sensors on a vehicle, autonomous and semi-autonomous vehicles mayuse HD maps to help navigate and to control a vehicle along its path.These HD maps may provide road geometry, lane geometry, road segmentrestrictions (e.g., speed limits), lane restrictions (e.g., turn-onlylanes), and any other information that may be related to the roadsegments of a road network. Further, HD maps may be dynamic and mayreceive updates periodically from map services providers which may beinformed by vehicles traveling along the road segments with sensorpackages able to identify and update the HD maps. Further, properties ofroad segments may change at different times of day or different days ofthe week, such as express lanes which may be in a first direction oftravel at a first time of day, and a second direction of travel at asecond time of day. HD maps may include this information to provideaccurate navigation and to facilitate autonomy along these road segmentsto supplement a sensor package associated with a vehicle.

According to example embodiments described herein, the role of HD mapsin facilitating autonomous or semi-autonomous vehicle control may be toimplement a differential policy enforcement tool based on individualvehicle capabilities, specifically with regard to sensor packages andthe level of sensor capabilities of a vehicle. Autonomous vehiclesleverage sensor information to determine safe regions on a road in whichthey may drive and use HD maps to plan safe routes from the vehicle'scurrent location to the destination. The HD map, whether stored locallyon a vehicle, such as in an ADAS, or stored remotely accessible vianetwork by the vehicle, may encode policies and restrictions such as thelane travel direction, speed limits, and other restrictions thatconstrain the vehicle to pre-described operation limits. Embodimentsdescribed herein implement a differential policy implementation for themap in the presence of manually, human-driven vehicles and uses the mapas a policy enforcement tool.

As autonomous vehicles transition from partial to full-autonomy, thepresence of manually driven vehicles with human drivers on the roads addan additional layer of complexity. In turn, the on-board sensor packageand autonomous control system needs to consider human behavior as anadded constraint to ensure the safety of passengers of the autonomousvehicle and other vehicles on the road. Further, the sensor suite ofautonomous and semi-autonomous vehicles may need to recognize road signsthat are human readable in context of the road situation. For example, asign occluded by a tree and missed by the on-board sensor package of avehicle will not be used to constrain the vehicle's speed as the vehiclemay infer that the sign is missing. In such scenarios, the HD map may beused to enforce policy constraints on allowable speed limits.Embodiments herein employ a use case where the HD map enforcesdifferential road policy where a set of policies and constraints forhuman drivers may not be equally applied to autonomous vehicles.

A differential policy set may be encoded by the HD map for autonomousand semi-autonomous vehicles, where different policies may be applied tovehicles based on their level of autonomy, which may be derived fromtheir sensor packages and levels of sensor capabilities of therespective sensor packages. The same set of road rules apply to bothautonomously driven vehicles and manually driven vehicles. However,vehicle performance and policies directed to vehicle control andperformance may be varied based on a level of capabilities of a vehicle.For instance, a sharp turn may have a suggested, reduced speed limit forvehicles as presented on signs proximate the turn. However, a fullyautonomous vehicle may be able to handle the turn at a higher speed thanthe suggested, reduced speed limit due to more advanced steering controland the ability of an autonomous vehicle to apex a turn properly due toa better understanding of the turn geometry from the HD map.

According to some embodiments, road signs as observed from a humandriver's standpoint may not be applicable to an autonomously drivenvehicle as the policy constraints for the autonomously driven vehiclemay be encoded in the HD map. The policies encoded into the HD map maybe distinct from those presented in signs to a user, as described above.

Further embodiments may encode different policies for different sensorpackages and levels of capabilities of vehicles. Embodiments may alsofactor in weather conditions with respect to policies encoded on an HDmap relative to autonomous and semi-autonomous vehicles. Vehicles havinga full complement of sensors may be capable of driving at a speed higherthan those that have a lower degree of sensor capability in inclementweather, where sensors of higher capability may mitigate the reducedvision available during inclement weather. Further, time of day mayaffect the policies encoded into an HD map. Vehicles having sensorpackages that include sensors capable of functioning well at night maybe able to travel at a higher speed than vehicles having sensors thatrely more on light to efficiently function.

Beyond the sensor capabilities and sensor packages of a vehicle,differential policies may be encoded in an HD map based on the dynamiccapabilities of a vehicle. For example, a large vehicle such as afull-sized truck may not be able to round a turn at a speed equal tothat of a small car, such that a policy for the small car may enable afaster speed through the turn. Further, vehicles with high efficiencybrakes, such as electric vehicles with regenerative braking which maybring a vehicle to a stop in a shorter distance than a conventionalvehicle with disc or drum brakes may abide by a policy in which afollowing distance to a leading vehicle may be shorter as the likelihoodof a rear end collision may be mitigated by the improved brakingcapabilities.

Vehicles of different sensor packages with different sensor capabilitiesmay have different policies applied by the HD maps described herein. TheHD maps described herein may be encoded with different policy levelsbased on a variety of factors, such as vehicle sensor package/sensorcapabilities, whether the vehicle is in autonomous control mode ormanual drive mode, the dynamic capabilities of the vehicle, the time ofday or weather conditions, the traffic levels near the vehicle, etc.These differential policies may provide improved safety among vehicleson the road, particularly when there is a mix of fully autonomousvehicles, semi-autonomous vehicles, and manually driven vehicles.Further, policies that are well matched and suited to a particularvehicle may enable that vehicle to perform optimally given theconditions, thereby improving driver and passenger experience.

FIG. 3 illustrates an example embodiment of an architecture specificallyconfigured for implementing embodiments described herein. Theillustrated embodiment of FIG. 3 may be vehicle-based, where informationregarding map data is provided via a map data service provider 108 andvehicle position along with navigation information is established basedon data received at the vehicle. As illustrated, the architectureincludes a map data service provider 108 that provides map data (e.g.,HD maps and policies associated with road links within the map) to theAdvanced Driver Assistance System (ADAS) 205, which may be vehicle-basedor server based depending upon the application. The map data serviceprovider may be a cloud-based 210 service. The ADAS receives navigationinformation and vehicle position and uses that information to map-match215 the position to a road link on a map of the mapped network of roadsstored in the map cache 220. This link or segment, along with thedirection of travel, is used to establish which HD map policies areapplicable to the vehicle associated with the ADAS, including sensorcapability information, autonomous functionality information, etc.Accordingly, policies for the vehicle are established based on thecurrent location and the environmental conditions (e.g., traffic, timeof day, weather). The HD map policies associated with the road segmentspecific to the vehicle are provided to the vehicle control, such as viathe CAN (computer area network) BUS (or Ethernet or Flexray) 240 to theelectronic control unit (ECU) 245 of the vehicle to implement HD mappolicies, such as various forms of autonomous or assisted driving, ornavigation assistance.

FIG. 4 illustrates a flowchart depicting a method according to anexample embodiment of the present invention. It will be understood thateach block of the flowcharts and combination of blocks in the flowchartsmay be implemented by various means, such as hardware, firmware,processor, circuitry, and/or other communication devices associated withexecution of software including one or more computer programinstructions. For example, one or more of the procedures described abovemay be embodied by computer program instructions. In this regard, thecomputer program instructions which embody the procedures describedabove may be stored by a memory device 26 of an apparatus employing anembodiment of the present invention and executed by a processor 24 ofthe apparatus 20. As will be appreciated, any such computer programinstructions may be loaded onto a computer or other programmableapparatus (for example, hardware) to produce a machine, such that theresulting computer or other programmable apparatus implements thefunctions specified in the flowchart blocks. These computer programinstructions may also be stored in a computer-readable memory that maydirect a computer or other programmable apparatus to function in aparticular manner, such that the instructions stored in thecomputer-readable memory produce an article of manufacture the executionof which implements the function specified in the flowchart blocks. Thecomputer program instructions may also be loaded onto a computer orother programmable apparatus to cause a series of operations to beperformed on the computer or other programmable apparatus to produce acomputer-implemented process such that the instructions which execute onthe computer or other programmable apparatus provide operations forimplementing the functions specified in the flowchart blocks.

Accordingly, blocks of the flowcharts support combinations of means forperforming the specified functions and combinations of operations forperforming the specified functions for performing the specifiedfunctions. It will also be understood that one or more blocks of theflowcharts, and combinations of blocks in the flowcharts, can beimplemented by special purpose hardware-based computer systems whichperform the specified functions, or combinations of special purposehardware and computer instructions.

FIG. 4 is a flowchart of a method for implementing differential policyenforcement of vehicles based on a level of sensor capability andautonomy of the respective vehicles. As shown, location information of avehicle is determined at 310 including a road segment along which thevehicle is traveling and a direction of travel of the vehicle. Sensorcapabilities of the vehicle are determined at 320. Based on the roadsegment along which the vehicle is traveling, an autonomous orsemi-autonomous policy for the road segment is determined specific tothe capabilities of the sensors of the vehicle at 330. Instructions forautonomous control of the vehicle are provided at 340 based on thedetermined autonomous or semi-autonomous policy determined.

In an example embodiment, an apparatus for performing the method of FIG.4 above may comprise a processor (e.g., the processor 24) configured toperform some or each of the operations (310-340) described above. Theprocessor may, for example, be configured to perform the operations(310-340) by performing hardware implemented logical functions,executing stored instructions, or executing algorithms for performingeach of the operations. Alternatively, the apparatus may comprise meansfor performing each of the operations described above. In this regard,according to an example embodiment, examples of means for performingoperations 310-340 may comprise, for example, the processor 24 and/or adevice or circuit for executing instructions or executing an algorithmfor processing information as described above.

Many modifications and other embodiments of the inventions set forthherein will come to mind to one skilled in the art to which theseinventions pertain having the benefit of the teachings presented in theforegoing descriptions and the associated drawings. Therefore, it is tobe understood that the inventions are not to be limited to the specificembodiments disclosed and that modifications and other embodiments areintended to be included within the scope of the appended claims.Moreover, although the foregoing descriptions and the associateddrawings describe example embodiments in the context of certain examplecombinations of elements and/or functions, it should be appreciated thatdifferent combinations of elements and/or functions may be provided byalternative embodiments without departing from the scope of the appendedclaims. In this regard, for example, different combinations of elementsand/or functions than those explicitly described above are alsocontemplated as may be set forth in some of the appended claims.Although specific terms are employed herein, they are used in a genericand descriptive sense only and not for purposes of limitation.

That which is claimed:
 1. An apparatus to facilitate autonomous orsemi-autonomous control of a vehicle comprising at least one processorand at least one non-transitory memory including computer program codeinstructions, the computer program code instructions configured to, whenexecuted, cause the apparatus to at least: determine locationinformation of a vehicle including a road segment and a direction oftravel; identify capabilities of sensors of the vehicle; access map datacomprising road segment policy information associated with the roadsegment, wherein the road segment policy information comprisespredefined operational limits for the road segment associated with themap data; determine an autonomous or semi-autonomous policy for the roadsegment specific to the vehicle based on the road segment policyinformation and in response to identifying the capabilities of thesensors of the vehicle; and provide instructions for autonomous controlof the vehicle based, at least in part, on the determined autonomous orsemi-autonomous policy for the road segment.
 2. The apparatus of claim1, wherein map data comprising road segment policy informationassociated with the road segment comprises different predefinedoperational limits for the road segment based on differing capabilitiesof sensors of vehicles.
 3. The apparatus of claim 2, wherein thedifferent predefined operational limits for the road segment based ondiffering capabilities of sensors of vehicles comprises relativelyhigher speed limits for fully autonomous vehicles.
 4. The apparatus ofclaim 1, wherein map data comprising road segment policy informationassociated with the road segment comprises different predefinedoperational limits for the road segment based on differing vehicletypes.
 5. The apparatus of claim 1, wherein the apparatus is furthercaused to: determine at least one of a time of day or a weathercondition, wherein causing the apparatus to determine an autonomous orsemi-autonomous policy for the road segment comprises causing theapparatus to determine an autonomous or semi-autonomous policy for theroad segment based, at least in part, on the determined time of day orthe weather condition.
 6. The apparatus of claim 1, wherein theapparatus is further caused to: determine a traffic level along the roadsegment in the direction of travel of the vehicle, wherein causing theapparatus to determine an autonomous or semi-autonomous policy for theroad segment comprises causing the apparatus to determine an autonomousor semi-autonomous policy for the road segment based, at least in part,on the determined traffic level along the road segment.
 7. The apparatusof claim 1, wherein road segment policy information associated with theroad segment differs based on a degree of autonomy of the vehicle. 8.The apparatus of claim 7, wherein road segment policy information isdynamically adjusted in response to a level of traffic on the roadsegment.
 9. The apparatus of claim 1, wherein causing the apparatus toidentify capabilities of sensors of the vehicle comprises causing theapparatus to identify types of sensors of the vehicle.
 10. A computerprogram product comprising at least one non-transitory computer-readablestorage medium having computer-executable program code instructionsstored therein, the computer-executable program code instructionscomprising program code instructions to: determine location informationof a vehicle including a road segment and a direction of travel;identify capabilities of sensors of the vehicle; access map datacomprising road segment policy information associated with the roadsegment, wherein the road segment policy information comprisespredefined operational limits for the road segment associated with themap data; determine an autonomous or semi-autonomous policy for the roadsegment specific to the vehicle based on the road segment policyinformation and in response to identifying the capabilities of thesensors of the vehicle; and provide instructions for autonomous controlof the vehicle based, at least in part, on the determined autonomous orsemi-autonomous policy for the road segment.
 11. The computer programproduct of claim 10, wherein map data comprising road segment policyinformation associated with the road segment comprises differentpredefined operational limits for the road segment based on differingcapabilities of sensors of vehicles.
 12. The computer program product ofclaim 11, wherein the different predefined operational limits for theroad segment based on differing capabilities of sensors of vehiclescomprises relatively higher speed limits for fully autonomous vehicles.13. The computer program product of claim 10, wherein map datacomprising road segment policy information associated with the roadsegment comprises different predefined operational limits for the roadsegment based on differing vehicle types.
 14. The computer programproduct of claim 10, further comprising program code instructions to:determine at least one of a time of day or a weather condition, whereinthe program code instructions to determine an autonomous orsemi-autonomous policy for the road segment comprise program codeinstructions to determine an autonomous or semi-autonomous policy forthe road segment based, at least in part, on the determined time of dayor the weather condition.
 15. The computer program product of claim 10,further comprising program code instructions to: determine a trafficlevel along the road segment in the direction of travel of the vehicle,wherein the program code instructions to determine an autonomous orsemi-autonomous policy for the road segment comprise program codeinstructions to determine an autonomous or semi-autonomous policy forthe road segment based, at least in part, on the determined trafficlevel along the road segment.
 16. The computer program product of claim10, wherein road segment policy information associated with the roadsegment differs based on a degree of autonomy of the vehicle.
 17. Thecomputer program product of claim 16, wherein road segment policyinformation is dynamically adjusted in response to a level of traffic onthe road segment.
 18. The computer program product of claim 10, whereincausing the apparatus to identify capabilities of sensors of the vehiclecomprises causing the apparatus to identify types of sensors of thevehicle.
 19. A method comprising: providing location information to aservice provider including a road segment and a direction of travel;providing sensor capability information to the service provider;determining location information of a vehicle including a road segmentand a direction of travel; receiving road segment policy informationfrom the service provider including predefined operational limits forthe road segment, wherein the road segment policy information isdetermined based, at least in part, on the sensor capabilityinformation; determining an autonomous or semi-autonomous policy for theroad segment based on the road segment policy information; and providingfor autonomous control of the vehicle based, at least in part, on thedetermined autonomous or semi-autonomous policy for the road segment.20. The method of claim 19, further comprising: providing at least oneof a time of day or a weather condition to the service provider, whereinroad segment policy information for the road segment is based, at leastin part, on the determined time of day or the weather condition.